US8274706B2 - System and method for halftone independent temporal color drift correction in hi-addressability xerographic printers - Google Patents
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/40—Picture signal circuits
- H04N1/407—Control or modification of tonal gradation or of extreme levels, e.g. background level
- H04N1/4076—Control or modification of tonal gradation or of extreme levels, e.g. background level dependent on references outside the picture
- H04N1/4078—Control or modification of tonal gradation or of extreme levels, e.g. background level dependent on references outside the picture using gradational references, e.g. grey-scale test pattern analysis
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/40—Picture signal circuits
- H04N1/40006—Compensating for the effects of ageing, i.e. changes over time
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- the present disclosure is directed to halftone independent temporal color drift correction, and more particularly to a system and method for such correction in hi-addressability xerographic printers.
- color is essential as a component of communication. Color facilitates the sharing of knowledge, and as a result companies involved in the development of digital color print engines are continuously seeking to improve the image quality of such products.
- One of the elements that affect image quality is the ability to consistently produce the same image quality on a printer over time. Colors on a printer tend to drift due to ink/toner variations, temperature fluctuations, type of media used, environment, etc. There has been a long felt commercial need for efficiently maintaining print color predictability, particularly as print media places greater importance on the accurate representation of merchandise in print and display media.
- CMY(K) patches The most popular technique to build a printer characterization transform involves printing and measuring a large set of color samples, i.e. CMY(K) patches, in conjunction with mathematical fitting and interpolation to derive CMY(K)->Lab mappings.
- the accuracy of the characterization transform clearly depends on the number (N) of patches printed and measured.
- N the number of patches printed and measured.
- these patches correspond to continuous tone CMY digital values, i.e. their binary representation is halftone dependent. Therefore, for color printers equipped with multiple halftone screens or halftone methods, the measurement and the correction has to be repeated as many times as the number of the halftones.
- FIG. 1 illustrates the measured TRCs for a 200 line per inch (lpi) halftone screen.
- the solid and the dashed lines represent the results from printouts on two different paper substrates, respectively.
- TRC line per inch
- temporal color drift of a printer can be corrected by a re-calibration of the color printer, quite often, by re-measuring and obtaining the tone response curves (TRCs) of the individual channels.
- TRCs tone response curves
- the color calibration process has to be repeated for each halftone selection.
- the native tone response of a halftone screen is seldom a smooth function.
- the required number of patches to print, or the number of digital levels cannot be too small. Therefore, it is believed beneficial to develop a halftone independent color drift correction method.
- Halftone independent color correction methods disclosed in above references are based on a 2 ⁇ 2 binary printer model for printers with isomorphic resolution up to 600 dpi.
- a fundamental assumption of the 2 ⁇ 2 printer model is that the rendered physical spot is no more than two logical image pixels wide.
- hi-addressability xerographic printers with printing resolutions much higher than 600 dpi violate this assumption.
- a halftone-independent color correction scheme was developed based on combining color predictions made using the 2 ⁇ 2 printer model for targets of varying resolution. Experiments conducted using two different 4800 ⁇ 600 hi-addressability printers confirm that the proposed color correction is very good and comparable to measurement and computation intensive halftone-dependent methods. Further benefits lie in the computational simplicity of the proposed scheme, and patch measurements that may be acquired by either a colorimetric device or a common desktop scanner.
- a model-based, halftone independent method for characterizing a high-addressability printer equipped with a plurality of halftone screens comprising: printing a target set of basic patches, said target set including patches having at least two resolutions and comprised of a fundamental binary pattern independent of a halftone screen; measuring printer response from the target set; modeling a halftone independent characterization of the printer with a mathematical transformation using the measured response; modeling a first halftone dependent characterization of the printer with the mathematical transformation to generate a first predicted result using a halftone screen; comparing a measured response of the printer using this halftone screen with the predicted result to define a correction factor corresponding to the halftone screen; and modeling a second halftone dependent characterization of the printer using a predicted response of the fundamental binary pattern and the correction factor.
- a halftone independent method for high-addressability device characterization comprising: calculating a binary printer model which is halftone independent; retrieving one of a set of user-selected halftones and a corresponding halftone correction factor; deriving a halftone correction factor as a mathematical transformation between a true color value as measured from the device, for at least two resolutions, and the predicted color value; processing a device color value using the selected halftone, the online binary printer model and a halftone correction factor to predict colorimetric values; and using the device color value and the predicted colorimetric values to produce an improved printer characterization for the user selected halftone.
- a high-addressability printing system equipped with a plurality of halftone screens, comprising: memory storing at least one set of basic patches, said set including patches having at least two resolutions; a marking system for printing a target set of basic patches, said target set including patches having at least two resolutions and comprised of a fundamental binary pattern independent of a halftone screen; a colorimetric device, said device measuring printer response from the target set; and a color balance controller, said controller using the measured response and modeling a halftone independent characterization of the printer with a mathematical transformation to generate a first predicted result using a halftone screen, said color balance controller, further comparing a measured response of the printer using this halftone screen with the predicted result to define a correction factor corresponding to the halftone screen, and modeling a second halftone dependent characterization of the printer using a predicted response of the fundamental binary pattern and the correction factor.
- FIG. 1 is a graphical illustration of exemplary measured TRCs for a halftone screen
- FIG. 2 is an illustrative example of possible embodiment for the disclosed system for carrying out the methods disclosed herein;
- FIG. 3 is a representation of an idealized non-overlapping printer model
- FIG. 4 is a representation of an exemplary circular-dot printer model
- FIG. 5 is an exemplary representation of a Two-by-two printer model in accordance with an aspect of the disclosed method
- FIGS. 6A-6G illustrate seven 2 ⁇ 2 calibration patches representing seven “solid” gray levels
- FIG. 7 illustrates seven 2 ⁇ 2 binary patterns defining seven “solid” levels for a single colorant printer (e.g., cyan) in accordance with the disclosed methods
- FIGS. 8A-8C are representative illustrations of “low-resolution” 2 ⁇ 2 patches for a typical 8 ⁇ high addressability printer as described herein;
- FIGS. 9-22 are graphical illustrations of various TRC curves for aspects of the disclosed embodiments.
- the disclosed system and methods are directed to the calibration of high-addressability printing systems.
- each output pixel represented by a rectangle 100
- the grid defining the output pixels is a conceptual coordinate for modeling purpose only. Any change on the grid, or the coordinate, will not affect the actual physical output of the printer at all. Therefore, it is possible to shift the grid to the position shown in FIG. 5 , so that each spot 200 , representing the physical output, is centered at one cross point of the grid 210 .
- the 16 different overlapping patterns can be further grouped into seven categories, G 0 to G 6 , as represented by the seven patches shown in FIGS. 6A-6G .
- the patches G 0 and G 6 are solid white and solid black, respectively.
- the patch G 1 is one of four different overlapping patterns, which are mirror images to each other.
- patch G 5 is also formed of four overlapping patterns.
- Each of the patches G 2 , G 3 and G 4 are one of two different overlapping patterns, which are also mirror images to each other. Therefore, in terms of the “ink” coverage, or the gray level, all pixels of each of the seven patches are identical. In other words, each patch only consists of one gray level at the pixel level, just like the solid white or black, and this gray level can be measured as exactly as any solid color.
- the ideal binary representations of the seven 2 ⁇ 2 patches are shown in FIG. 7 .
- the 2 ⁇ 2 printer model can be used to predict the gray output of any binary pattern.
- the output of the binary pattern in FIG. 3 can be illustrated by FIG. 5 using the 2 ⁇ 2 printer model and described by Table 1, where G 0 -G 6 are the measured gray levels from one of the corresponding seven 2 ⁇ 2 patches T 0 -T 6 , respectively (i.e., binary output illustrated in FIG. 3 represented as one of seven 2 ⁇ 2 patterns for each cell in the table).
- the 2 ⁇ 2 printer model uses the Neugebauer equation with the Yule-Nielson modification as follows:
- n 1 is the number of pixels of the corresponding 2 ⁇ 2 patch in the given binary pattern
- ⁇ is the Yule-Nielsen factor, which is often chosen as a fitting parameter.
- the color 2 ⁇ 2 printer model can be described in a similar manner and can be found in the references noted previously.
- the 2 ⁇ 2 printer model can predict the color appearance of any binary patterns for a given color printer and the color accuracy of the prediction by the 2 ⁇ 2 model is very high for printers with relatively uniform spot shapes, for example inkjet printers.
- Color correction or calibration algorithms typically use the response of a printer along each (e.g. C, M, Y, K) of its colorant channels.
- the monochrome 2 ⁇ 2 model can successfully be employed for predicting color response of the printer along the individual colorant channels.
- Xerographic printers usually do not generate uniform round-shape spots for isolated single pixels and the dot overlapping is more complicated than inkjet outputs.
- the 2 ⁇ 2 printer model applied to a xerographic printer may yield larger prediction errors.
- modeling of these systematic errors leads to aspects of the disclosed color correction scheme. For example, in previous work on temporal drift correction (e.g., co-pending Ser. No. 11/343,656 by S.
- R ⁇ true ⁇ ( t 2 , i , H ) R true ⁇ ( t 1 , i , H ) R 2 ⁇ 2 ⁇ ( t 1 , i , H ) ⁇ R 2 ⁇ 2 ⁇ ( t 2 , i , H ) Eq . ⁇ 5
- R ⁇ true ⁇ ( t 2 , i , H ) R 2 ⁇ 2 ⁇ ( t 2 , i , H ) R 2 ⁇ 2 ⁇ ( t 1 , i , H ) ⁇ R true ⁇ ( t 1 , i , H ) Eq . ⁇ 6
- a particular printer device can be characterized with a reduced number of CMY test target color values 80 for a particular halftone screen pattern 82 by using the disclosed model determined offline with the fundamental binary pattern that is halftone independent 84 , 86 and a correction factor (e.g., sum of weighting factors of at least two resolutions) that has been previously derived offline and then stored for correspondence to the selected halftone screen 82 .
- the true color values of the printing device are measured 90 and in error metric calculation, ⁇ E ab 92 is calculated for use in the transform for characterizing printing system operation.
- Printing may be carried out by a marking system for printing a target set of patches, including patches having at least two resolutions and comprised of a fundamental binary pattern independent of a halftone screen. Measurement as referenced in 90 may be completed by a colorimetric device, the device measuring printer response from the target set, wherein a color balance controller uses the measured response and modeling a halftone independent characterization of the printer with a mathematical transformation.
- an estimate of the true printer response at a drifted printer state t 2 could be accurately determined by printing and measuring only the halftone independent 2 ⁇ 2 patches (7 for each colorant and 25 for a 4 color printer; discounting the repeated measurements of the white patch).
- the crucial assumption in the equation above is that the functional mapping from the 2 ⁇ 2 predicted response does not depend on time. Physically, such a modeling is motivated by the fact that the difference between the 2 ⁇ 2 printer model and the true measured response is attributed to the geometric assumptions made by the model.
- FIGS. 8A-8C show, respectively, “low-resolution” 2 ⁇ 2 patches for a typical 8 ⁇ high addressability printer used in experiments (e.g., where resolution in one direction is eight times the resolution in the perpendicular direction)-respectively illustrating a cyan channel at resolutions of 600, 1200 and 2400 ⁇ 600.
- FIGS. 8A-C it is possible to obtain low-resolution 2 ⁇ 2 predictions by pixel replication of the 2 ⁇ 2 binary patterns in the digital file, and subsequently obtain macroscopic measurements of the printed patch.
- FIGS. 9 and 10 plot the 2 ⁇ 2 predicted response (solid) and the true printer response (dashed) for the Magenta channel at default (t 1 ) and drifted (t 2 ) printer states.
- a 175 lpi clustered dot halftone screen was employed. Both responses are in deltaE ( ⁇ E) from paper and for a 4800 ⁇ 600 (i.e. 8 ⁇ hi-addressability), for example a xerographic printer.
- the 2 ⁇ 2 prediction in FIGS. 9 and 10 is obtained by printing and measuring the 2 ⁇ 2 patches at 1 ⁇ resolution (i.e. 600 ⁇ 600 binary and scaled by a factor of 8). Similar plots for resolutions 2 ⁇ and 4 ⁇ are shown in FIGS. 11-12 and FIGS. 13-14 , respectively.
- FIG. 15 depicted therein is the estimated (solid line) 2 ⁇ 2 response from using Equation 7 versus the true measured hi-addressability (dashed line) response. As is evident from FIG. 15 , there is a near perfect overlap between the true (dashed) and estimated (solid) responses.
- FIGS. 16 through 22 Similar plots and the corresponding correction for the Cyan channel of another xerographic hi-addressability printer are shown in FIGS. 16 through 22 .
- a 200 lpi clustered dot screen was used for the halftone. More specifically, FIG. 16 illustrates the True Hi-Addressability printer response versus the 0.5 ⁇ 2 ⁇ 2 prediction: default state t 1 , and FIG. 17 the same at drifted state t 2 .
- FIG. 18 shows the True Hi-Addressability printer response versus the 1 ⁇ 2 ⁇ 2 prediction at default state t 1 , and FIG. 19 the same at drifted state t 2 .
- FIG. 20 and 21 respectively show the default (t 1 ) and drifted (t 2 ) states for True Hi-Addressability printer response versus the 2 ⁇ 2 ⁇ 2 prediction
- FIG. 22 shows the True Hi-Addressability printer response versus the estimated response for drifted state t 2 .
- Equation 7 The salient features of the proposed correction in Equation 7 (Note: Eq. 7 is a generalization of Eq. 6, where only one resolution is used and the corresponding weight is equal to one) may be summarized as:
- These weights are in general optimized based on data from multiple printer states—however, this optimization needs to be carried out only once (offline) and once the weights are determined they may be used, as is, in real-time calibration paths. It is contemplated that such weights may be stored, for example, in a memory associated with color balance controller as represented by a printer ( FIG. 2 ; 90 ).
- a color correction method for a four-color printer is enumerated as follows. The method may be executed, for example, on the systems depicted in the embodiments of FIGS. 2 A,B in accordance with pre-programmed instructions, or via other computing platforms associated with a printing system.
- the foregoing steps may also be characterized in a more general form, wherein the targets of the at least two resolution patches are printed with the halftone independent pattern and then measured to identify the printer response to the target. Separate measurement is accomplished by conventional means for spectral photometric devices.
- a halftone independent characterization of the device can then be modeled offline with a mathematical transformation comprising the measured response. “Offline” is intended to mean that the characterizing process is performed other than when the printer is performing a user/customer specified task in an ordinary work environment, whereas “online” is such a customer environment.
- a halftone screen dependent characterization is then modeled with the mathematical transformation to generate the predicted result. The predicted result is compared with a true color measured response to obtain a correction factor for the employed halftone screen print.
- a second halftone dependent characterization of the printer can then be modeled using the mathematical transformation and the correction factor.
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Abstract
Description
TABLE 1 | ||||||||
G1 | G2 | G1 | G1 | G1 | G1 | G1 | ||
G1 | G2 | G1 | G1 | G1 | G1 | G1 | ||
G0 | G1 | G2 | G2 | G1 | G0 | G0 | ||
G0 | G3 | G5 | G2 | G4 | G1 | G0 | ||
G1 | G5 | G3 | G0 | G1 | G4 | G1 | ||
G2 | G6 | G5 | G1 | G1 | G4 | G1 | ||
G1 | G2 | G2 | G1 | G1 | G1 | G0 | ||
where Gi, i=0 to 6, is the measured gray level of each of the seven 2×2 patches, n1 is the number of pixels of the corresponding 2×2 patch in the given binary pattern, and γ is the Yule-Nielsen factor, which is often chosen as a fitting parameter. As a further example, the average gray level of the binary pattern shown in
G AVG=(7G 0 1/γ+25G 1 1/γ+8G 2 1/γ+2G 3 1/γ+3G 4/γ+3G 5 1γ +G 6 1/γ)γ Eq. 2
R true(t,i,H)=f(R 2×2(t,i,H)) Eq. 3
where Rtrue(t,i,H)=true/measured response of ith colorant at time t, R2×2(t,i,H)=2×2 predicted response of ith colorant at time t and H represents the halftoning method used, i=C, M, Y, K
where Rtrue(t,i,H)=true/measured response of ith colorant at time t in deltaE from paper;
-
- R2×2(t,i,H)=2×2 predicted response of ith colorant at time t in deltaE from paper; and
- H represents the halftoning method used, i=C, M, Y, K.
The illustrated relationship states that, given the knowledge of the 2×2 and true/measured printer response at a default or reference printer state t1, it is possible to estimate the true response at a drifted state t2 as:
where i, H are as before and j denotes the resolution of the 2×2 prediction; as an example for an 8× hi-addressability printer j=1×, 2×, 4× etc.
-
- A. Print and measure a plurality (e.g., seven) 2×2 patches shown in
FIG. 7 at the required number of resolutions (at least two); - B. For each halftone screen or method:
- 1. To get a 2×2 TRC estimation, for each constant input digital level:
- a. Derive the output binary pattern;
- b. Use the 2×2 printer model to interpret the binary pattern as a seven-level gray image;
- c. Use Eq. 1, and the measurement of seven 2×2 patches, to get the average output;
- 2. Store the 2×2 TRC predictions at t1 and for each resolution into the memory;
- 3. Obtain the true TRC by printing and measuring the outputs of different levels and store the true TRC into the memory.
II. Later, at a time t2 (drifted printer state), and
- 1. To get a 2×2 TRC estimation, for each constant input digital level:
- A. Print and measure a plurality (e.g., seven) 2×2 patches shown in
-
- A. Print and measure the seven 2×2 patches shown by
FIG. 7 at the required number of resolutions; - B. For each halftone screen or method:
- 1. To get a 2×2 TRC estimation, for each constant input level:
- a. Derive the output binary pattern;
- b. Use the 2×2 printer model to interpret the binary pattern as a seven-level gray image;
- c. Use Eq. 1, and the measured result from the step 2 a to get the average output;
- 2. Calculate the correction factor (e.g., sum of weighting factors of at least two resolutions) as in the large square brackets in Eq. 7 (for each digital level) by using the 2×2 TRC estimation at t2 and the 2×2 estimation stored at the initial time t1;
- 3. Apply the correction obtained above to the true TRC stored at t1 (I.3.) to predict the true TRC at the new time t2
- 4. Make a corresponding adjustment to the input image based on the predicted true TRC for correcting the color drift.
- 1. To get a 2×2 TRC estimation, for each constant input level:
- A. Print and measure the seven 2×2 patches shown by
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EP10150479.3A EP2209297B1 (en) | 2009-01-16 | 2010-01-12 | System and method for halftone independent temporal color drift correction in hi-addressability xerographic printers |
JP2010003788A JP2010166563A (en) | 2009-01-16 | 2010-01-12 | System and method for halftone independent temporal color drift correction in xerographic printer having high addressability |
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US20120327433A1 (en) * | 2011-06-21 | 2012-12-27 | Edge Christopher J | Method of designing a color chart |
US20130208289A1 (en) * | 2012-02-15 | 2013-08-15 | Nobuyuki Satoh | Color measuring device, image forming apparatus, color measuring method, and color measuring system |
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JP2010166563A (en) | 2010-07-29 |
US20100182616A1 (en) | 2010-07-22 |
EP2209297A1 (en) | 2010-07-21 |
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